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library(gplots) 
library(Seurat)
#all10x <- readRDS('output/10x-180504')
brown_markers <- read.table('/projects/pytrik/sc_adipose/analyze_10x_fluidigm/data/markergenes/180504/markers_10x-180504_brown', header=T)
brown_markers <- brown_markers[brown_markers$p_val_adj < 0.05,]
brown_markers_pos <- brown_markers[brown_markers$avg_logFC > 0.25,]
brown_markers_neg <- brown_markers[brown_markers$avg_logFC < -0.25,]
white_markers <- read.table('/projects/pytrik/sc_adipose/analyze_10x_fluidigm/data/markergenes/180504/markers_10x-180504_white', header=T)
white_markers <- white_markers[white_markers$p_val_adj < 0.05,]
white_markers_pos <- white_markers[white_markers$avg_logFC > 0.25,]
white_markers_neg <- white_markers[white_markers$avg_logFC < -0.25,]
getIntersectingGenes <- function(df, depot){
  samples <- as.character(unique(all10x@meta.data$sample_name[all10x@meta.data$depot == depot]))
  genes <- df[df$sample_name == samples[1], 'gene']
  for (sample in samples[2:length(samples)]){
    genes <- intersect(genes, df[df$sample_name == sample, 'gene'])
  }
  print(paste('Nr of genes for ', depot, ': ', length(genes), sep=''))
  return(genes)
}
#Peri 
peri_pos <- getIntersectingGenes(brown_markers_pos, 'Peri') #12
[1] "Nr of genes for Peri: 12"
peri_neg <- getIntersectingGenes(brown_markers_neg, 'Peri') #9
[1] "Nr of genes for Peri: 9"
#Supra
supra_pos <- getIntersectingGenes(brown_markers_pos, 'Supra') #4
[1] "Nr of genes for Supra: 4"
supra_neg <- getIntersectingGenes(brown_markers_neg, 'Supra') #3
[1] "Nr of genes for Supra: 3"
#Visce
visce_pos <- getIntersectingGenes(white_markers_pos, 'Visce') #4
[1] "Nr of genes for Visce: 1"
visce_neg <- getIntersectingGenes(white_markers_neg, 'Visce') #25
[1] "Nr of genes for Visce: 25"
#Subq
subq_pos <- getIntersectingGenes(white_markers_pos, 'Subq') #4
[1] "Nr of genes for Subq: 4"
subq_neg <- getIntersectingGenes(white_markers_neg, 'Subq') #7
[1] "Nr of genes for Subq: 7"

Perirenal

VlnPlot(all10x, features.plot=peri_pos, group.by='sample_name', point.size.use=-1, nCol=2, x.lab.rot=T, size.x.use=10)

VlnPlot(all10x, features.plot=peri_neg, group.by='sample_name', point.size.use=-1, nCol=2, x.lab.rot=T, size.x.use=10)

Supraclavicular

VlnPlot(all10x, features.plot=supra_pos, group.by='sample_name', point.size.use=-1, nCol=2, x.lab.rot=T, size.x.use=10)

VlnPlot(all10x, features.plot=supra_neg, group.by='sample_name', point.size.use=-1, nCol=2, x.lab.rot=T, size.x.use=10)

Visceral

VlnPlot(all10x, features.plot=visce_neg, group.by='sample_name', point.size.use=-1, nCol=2, x.lab.rot=T, size.x.use=10)

Subcutaneous

VlnPlot(all10x, features.plot=subq_pos, group.by='sample_name', point.size.use=-1, nCol=2, x.lab.rot=T, size.x.use=10)

Check markers in new data

data <- readRDS('output/10x-180831')

TM4SF1: pos for peri \ LINC01116: pos for peri/neg for visce \ TIMP3: neg for peri \ THBS1: neg for peri/pos for subq \ HOXB7: neg for supra \ BARX1: pos for visce. Not found for all visceral samples however.\ PPAP2B THBS1: pos for subq DKK1: pos for subq

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